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• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Study EGAS00001003973

• cfDNA methylation dataset for colon cancer

  Enzymatic conversion-based methylation sequencing data (EM-seq) for colon cancer used in the MESA study

  Dataset EGAD50000000075

• PASCAL-MID Data Access Committee

  DAC for the center of Personalized Approach to Genome Editing of Stem Cells for Autotransplantation of Monogenic Immunodeficiencies (PASCAL-MID) at Aarhus University and Aarhus University Hospital

  Dac EGAC50000000680

• Pancreatic Cancer NGS WGS data

  Whole genome sequencing data for Pancreatic Cancer Samples exploring the tandem duplicator phenotype

  Study EGAS50000001078

• V4_Colorectal_panel_test

  Targeted gene screen of cell line tumours for testing the new V4 Colorectal gene panel.

  Study EGAS00001001807

• Dataset for B-ALL scRNA-seq

  10x Genomics 5' library scRNA-seq data for 85 B-ALL patients with different subtypes

  Dataset EGAD00001011327

• WGBS data for Glioblastoma (EGAS00001003953, H016)

  Whole Genome Bisulfite data for human glioblastoma patients, EGAS00001003953. 68 human samples

  Dataset EGAD00001006546

• A98269B

  Whole genome sequencing for single cells for library A98269B 1609 cells; filetype=bam

  Dataset EGAD00001006947

• A96217B

  Whole genome sequencing for single cells for library A96217B 1616 cells; filetype=bam

  Dataset EGAD00001006945

• ChIP-Seq files for PCGP ATRX study

  ChIP-Seq files for PCGP ATRX study paper titled "MYCN Amplification and ATRX Mutations are Incompatible in Neuroblastoma"

  Dataset EGAD00001004429